Offender-based policing has been shown to be an effective strategy for crime reduction across the country. However, a key challenge in such efforts is the problem of identifying which offenders should be targeted for intervention or proactive policing outreach. Scoring and ranking offenders usually requires extensive manual collation and calculation using databases and spreadsheets. Because of the labor required to create and maintain an offender ranking and scoring system, the information is often out of date as well.

The Lumen Dynamic Scoring Agent is designed to solve this problem. It automatically scores and ranks offenders based on their past involvements in events, using live data that is updated continuously. The results are efficiently scored and ranked at query time so that the user can see the most up to date information on demand.

A significant benefit of the Dynamic Scoring Agent is that the scoring algorithm allows users to incorporate their own preferences at query time, so that the scored and ranked results reflect those user preferences. This means that the particular crimes of interest to an agency or an individual can be selected and used in the ranking criteria dynamically – the user is not limited to a “canned” ranking that cannot be changed or edited. For example, a single agency can easily produce separate lists of violent offenders, property crime offenders, and motor vehicle theft offenders (and more) and keep those lists up to date with minimal effort.

Furthermore, offender involvements across disparate data sources from multiple agencies are integrated on the fly, so that the user gets a complete awareness of offender scores and activities, regardless of how many data sources or jurisdictions are involved. By automatically correlating offender and event data across multiple data sources, the Dynamic Scoring Agent dramatically reduces the time required to produce a top offender list.

Once a ranked and scored list is created, the Dynamic Scoring Agent automatically keeps the list up to date and allows users to see new activity for any offender on the list. This enables agency-wide offender-based policing strategies to efficiently monitor and adapt as new information becomes available.

Facial recognition is a technology that seems like it will soon be everywhere, from unlocking one’s phone to checking in for a flight at the airport. A fast food restaurant in China now allows diners to “Smile to Pay,” using facial recognition to identify the customer and deduct payment from his or her account automatically.1 Multiple airlines are currently testing facial recognition at some gates to eliminate the need for even an electronic boarding pass.2

As one might imagine, governments worldwide are also adopting facial recognition software. Police in the United Kingdom used a police van equipped with facial recognition technology to recognize and arrest a wanted man on the street.3 The Chinese government is even using it to identify frequent jaywalkers at major intersections.4

Law enforcement professionals in the United States have been using facial recognition for a number of years now. The FBI’s Next-Generation Identification Interstate Photo System (NGI-IPS), for example, first operated as a pilot program in 2011 before becoming fully operational in 2016. Part of a larger biometrics system the FBI runs that will cost over $1 billion to fully deploy, NGI-IPS contains more than 30 million photos that can be searched using facial recognition technology.5

Many state and local agencies have procured their own solutions as well, but deployment has typically been limited to only the largest agencies due to budgetary constraints. However, with the rise of new facial recognition technology that is both more affordable and better than what came before, law enforcement agencies that previously could not afford it might now be able to acquire their own facial recognition solutions. They might also be able to deploy the technology in ways that were previously impossible, such as on a mobile phone, body camera, or dash cam.

Facial Recognition FAQs

Before acquiring facial recognition technology, agencies should understand what the technology is capable of and how it can be used, including the answers to these common queries.

What is facial recognition?

Facial recognition uses image processing and machine learning algorithms to match a photo of an unidentified person (a “probe” photo) against a database of photos of identified persons. Most face identification algorithms will typically produce a list of possible matches, with each match having a score that indicates the quality or likelihood of a match.

Low resolution, poor lighting, motion blur, glare, off-angle faces (tilted, turned to the side, looking up or down), facial hair, glasses, hats, and other details of the probe photos can challenge algorithms to produce a good match. Advances in technology based on algorithms such as “deep learning,” however, have produced significant gains when processing challenging probe photos. The best systems will likely surpass human capabilities for facial recognition in the near future.

What is face detection?

In face detection, the algorithm attempts to detect faces in an image, without necessarily identifying whose face it is. It may also locate features, such as eyes, nose, mouth, and ears; detect the presence of beards, mustaches, eyeglasses, and hats; and identify gender, race, approximate age, and emotional state. This can be used for many different purposes, including gathering statistics on a large group of people (such as visitors to a building), measuring the reaction of people to a new product, or even determining the possible intent of individuals in a crowd. Many facial recognition algorithms are capable of face detection as well.

What are the law enforcement uses of facial recognition and face detection technology, and how does the public perceive them?

Public perception is an important aspect to consider whenever new technology becomes available to law enforcement. Even though the technology may be perfectly legal when used in appropriate circumstances, lack of information or even misinformation can cause a negative reaction on the part of the public. As a result, it is important for law enforcement decision makers to fully understand the spectrum of possible uses of the technology, as well as how the public may perceive those uses.

The simplest and most common use of facial recognition software is to search a database of known offenders for matches of an unidentified suspect in a criminal incident. A prime example of this is a security camera video image of a suspect shoplifting at a retail store. Detectives confront similar scenarios on a regular basis and often have little evidence to go on other than the video and perhaps an eyewitness who might not remember much. However, it is unlikely that even the best facial recognition system would generate just a single match from a security camera photo. Instead, the system will generate a list of possible matches, and the detectives working the case will need to use standard investigative methods to either rule out or further investigate each match, as they would with any investigative lead.

Facial recognition holds the promise to generate leads on a great many such cases that might otherwise go unsolved. Each case might not be especially high profile, but, in aggregate, these cases represent a staggering amount of criminal activity. Given that, even a modest increase in closure rates would be significant. Shoplifting, for example, generates billions of dollars in losses every year in the United States, where there are estimated to be almost a million “professional” shoplifters operating, including international shoplifting rings.6 Stopping even a single shoplifter could prevent tens of thousands of dollars in future theft.

There are numerous other examples of rarer but higher profile crimes, ranging from terrorism to mass shootings to kidnapping cases, in which the only initial clue to the suspect’s identity was a security camera photo. Although the cases are different, the use of facial recognition in these cases is essentially the same: identify an unknown suspect by searching a photo against a database of known offenders.

As facial recognition technology advances, however, other uses may become more widespread. Potentially, these could include the following capabilities:

• Match an unidentified suspect photo obtained in association with a criminal incident with a state database of driver’s license photos.• Match a photo taken with permission (of a suspect or field contact, for example) using an officer’s smartphone with a database of driver’s license or jail booking photos.• Search in real time to match people entering a courthouse with a database of wanted person photos.• Perform a real-time search of airport travelers to match with a database of known terrorists.• Search in real-time from a vehicle-mounted camera to match passersby with a database of wanted person photos.• Search in real-time from a vehicle-mounted camera to match and record the likely identity, time, and location of passersby using a database of driver’s licenses and state identification photos.

Many of these capabilities are already a reality today. The key differences between all of these uses come down to two questions: (1) Where and how did law enforcement obtain the probe photo? (2) Where and how did law enforcement obtain the database of photos?

The easiest scenario to explain to the public is when both the probe photo and the database are obtained in direct association with criminal activities. If the probe photo is a security camera image and the database is a set of jail booking photos, for example, even the most ardent privacy rights advocate would probably find this use acceptable. If the probe photo is of a person with no known or suspected criminal activity and the database is also a non-criminal database, however, one can imagine the potential for public outcry.

By comparison, consider some possible uses of facial recognition in commercial environments, which are already a reality today:

• Pay at a fast-food restaurant.• Automate driver check-in for ride-sharing services.• Check in for a flight without a boarding pass.• Automatically identify known customers in a retail store, storing their browsing habits, attention, and estimated emotional state for later analysis.• Automatically identify known shoplifters or disgruntled former employees in a retail store and alert store security.

While commercial firms do not have the law enforcement powers of government, they also do not operate under the same legal framework or strictures as a government. As a result, they can often engage in practices that would be inadvisable or even illegal for a government entity. Several of the examples above illustrate this point clearly. When considering facial recognition technology for a law enforcement agency—and when answering questions from the public on how an agency uses such technology—it can be useful to understand the extent to which commercial firms are racing far ahead of many governments.

Can facial recognition be used in the cloud?

Finally, as more agencies move to using cloud solutions to reduce costs and improve reliability, it is natural to ask if facial recognition can be done in the cloud. Facial recognition used to require an on-premise deployment on an agency’s own servers, but that is no longer the case. More and more providers of facial recognition software offer their solutions in a cloud deployment, which means that there is no software to install and no servers to manage. The key questions to address are how secure the cloud provider is and what the provider’s stance is with respect to CJIS compliance (in the United States) or applicable regulations in the agency’s country. There are multiple cloud providers today offering facial recognition in a CJIS-compliant cloud environment.

Clearly, facial recognition software has come a long way and can play a critically important role in law enforcement in the future. Therefore, it is essential for law enforcement agencies to take proper precautions, both in purchasing and using this technology. Preparing the public for how facial recognition software works, what it can (and can’t) do, and how it can have a positive impact on reducing crime will go a long way toward creating an atmosphere of cooperation and trust.

Don Wick recently retired as chief of the Arvada, Colorado, Police Department. He currently serves as director of operations at Numerica Corporation, where he focuses on Lumen, Numerica’s law enforcement search, analysis, and data sharing platform.

Numerica Corporation – which develops intuitive law enforcement database software, crime analysis software, and analytics – announced today that it has been awarded an Information Technology Schedule 70 contract by the General Services Administration (GSA).

The GSA is the premier procurement arm for all federal government agencies. Under the new contract, federal, state, and local government agencies will be able to access Numerica’s solutions via GSA Advantage!®, the government’s electronic online ordering system, at www.gsaadvantage.gov.

Through GSA contract number 47QTCA18D00AB, Numerica will offer its Lumen Desktop, Mobile, and Enterprise solutions, as well as professional services and training, to government agencies.

Lumen Desktop provides a powerful, but easy-to-use interface to rapidly focus criminal and intelligence investigations and analysis on the most relevant people, places, and events. Lumen Desktop users can also search, analyze, and share data, produce photo lineups, automatically create link charts, and map disparate data sources. Lumen Mobile is a simple mobile interface which enables patrol, detectives and other officers in the field to quickly and easily find information related to any entity from a smartphone or tablet.

“We are extremely proud to be awarded the GSA certification,” says Nick Coult, Senior Vice President of Law Enforcement at Numerica. “While Numerica has grown exponentially over the past few years, the GSA contract will take us to a whole new level, expanding our government business while we continue to provide our clients with exceptional solutions and service.”

Come see us at the Department of the Navy FST event this week! Stop by booth 103 in the Woodrow Wilson room to see the latest in Numerica’s Air & Missile Defense and Space Situational Awareness solutions.

We’ll be in Anaheim for the 2018 LEIU/IALEIA Training Event this week. Make sure to stop by Booth 110 to see the newest solutions from Lumen that are transforming investigations and offender-based policing.

The Mesa County,Colorado Sheriff’s Officewasexperiencing a marked increase in crime, particularly in the areas of property crime, homicide, and sexual assault. Theoffice also recognized that there was a significant gap between the data contained in its information management system and the information that was readily availableto its deputies on the street.

THEGOAL

Increase the use ofcrime-related data

Change the way the officewas visualizing criminal activity

Track criminals (and the crimes theycommit) as theytravel from jurisdiction to jurisdiction

NUMERICA’SAPPROACH

Used modern webtechnologyto bring all of the office’s data sourcesinto a single, integratedsystem

Changed the way the officewas looking at criminal activity by enabling it totrack and overlay data, identify trends and “hot spots” for criminal activity, and track criminal movement

RESULTS

Drove the office’s response to crime byallowing it to shift to a more intelligence-led approach to policing, which allowed patrols toconnect data to crimes and gather information in real-time

Produced a 31% reduction in property crime in high-crime areas

Reduced calls for service, enabling the officetogive more attention and staffing togeographic areas in which criminal activity was the highest

“Lumen has fundamentally changed our Sheriff’s Office and the way we look at crime.”
“Lumen has driven our response to crime, revolutionizing the way we handle day-to-day activities.”

-Sheriff Matt Lewis

https://www.numerica.us/wp-content/uploads/2018/03/Mesa-Lewis-Picture-2.jpg502500Numericahttps://www.numerica.us/wp-content/uploads/2014/11/logo1.pngNumerica2018-03-22 09:51:012018-05-02 13:55:51Case Study: How the Mesa County Sheriff’s Office Used Lumen to Implement an Intelligence-Led Approach to Policing to Reduce Preventable Crime by 31% in High-Crime Areas.

The Denver Police Department has signed an enterprise-wide upgrade of Lumen – a state-of-the-art data sharing software that combines access to real-time data with advanced analytics – to enhance data-driven law enforcement activities for more effective policing.

Developed by Colorado-based Numerica Corporation, Lumen enables the entire Denver Police Department, including more than 1,400 sworn officers and numerous civilian employees, to search, analyze, and share crucial law enforcement data from multiple databases across multiple jurisdictions with a single click.

“The Denver Police Department has seen organic growth in the use of Lumen over the last 12 months, and with the Enterprise upgrade, they will have access to the Lumen suite agency-wide,” explains Nick Coult, Senior Vice President of Law Enforcement at Numerica. “Lumen gives patrol officers and detectives on the street access to the latest offender and suspect information – including booking photos, known associates, vehicle and incident information, and other key details – directly on their smartphones.”

“At the same time, it empowers commanders to lead with data-driven strategies and tactics,” Coult continues. “Crime-prevention initiatives are nothing without tangible results. That’s where Lumen comes in, not only turning insight into action, but increasing operational effectiveness and providing the data to prove it.”

The Denver Police Department uses the entire suite of Lumen applications, which includes:

Lumen Mobile, a simple mobile interface which enables users on a smartphone to quickly and easily find information related to any entity.

“With Lumen, the Denver Police Department will have an enterprise search and analytics platform specifically designed to meet the needs of law enforcement,” Coult concludes. “That means it is a secure product that is compliant with the FBI’s Criminal Justice Information Services Policy. It is fast, with search results appearing in seconds or less. And it is easy to get started, with minimal IT requirements and an intuitive interface.”

Numerica delivers state-of-the-art defense and law enforcement solutions to both government and industry customers. For its law enforcement customers, Numerica provides mission-critical insights to law enforcement, intelligence, and security professionals through the development of intuitive law enforcement database software, crime analysis software, and analytics.

We just published our case study on how we helped the Colorado Information Sharing Consortium implement a next-generation data sharing system for over 60 agencies, representing over 8,000 officers and 300 million law enforcement records. Click here to download.

In this Lumen blog, let’s hear from a crime analyst working on a difficult case and a search for critical connective information:

“We were working on a domestic violence case with a stolen handgun. According to the victim, the suspect put the stolen handgun in the victim’s mouth and pulled the trigger, but luckily, the gun did not fire. We knew the circumstances surrounding the theft of the handgun, but did not know the specific case. I searched Lumen for cases involving some of the specifics of the case and within 30 seconds I was reading the theft case report from another agency. This allowed us to validate the victim’s side of the domestic violence story, help another agency solve a weapons theft, and charge a suspect.”

No connections would’ve been made and no suspects would’ve been charged in this case if it weren’t for accessible and organized data. In this blog, the crime analysis software experts at Numerica will break down how top-of-the-line software like Lumen can help crime analysts connect the dots in critical cases, and discover big-picture trends and patterns in the law enforcement system and the public at large.

Identify Trends and Patterns

While commanders and patrol officers are responsible for stopping and preventing crime and handling heat-of-the-moment situations, crime analysts look at crime and police activity with a much wider lens. They’re an integral part of law enforcement agencies, helping them to identify key patterns, trends, and “hot spots” as they emerge.

Crime analysts with the right tools can stop widespread crime before it becomes widespread—for example, crime analysts might notice two recent convenience store burglaries within the same police jurisdiction, and can relay that information to commanders and patrol officers so they can remain proactive, keep the public informed, and hopefully stop the next burglary from taking place.

Crime analysts also have the ability to recognize long-term patterns. Perhaps they discover there’s been a rise in car accidents at a certain intersection over the past few years, or maybe they notice a certain neighborhood has a much larger number of drug arrests than the surrounding areas. Whatever the case, finding these short-term or long-term patterns would be impossible without data that can be accessed, organized, and manipulated.

That’s the power of Lumen. Compile law enforcement data across multiple jurisdictions, organize data to identify trends and patterns across geographic areas or suspect groups, and use that newfound knowledge to empower patrol officers and close cases.

Access Information Fast

Sometimes, finding and delivering information must happen at a moment’s notice in order to connect the dots on a case or book a suspect—and if you can’t find the information you need quickly and efficiently, your law enforcement agency might fall short and run out of time when it matters the most.

With Lumen, data is accessible from an easy-to-use web platform, so anyone within your agency can find the data they need. No switching between data portals or calling faraway agencies for data—with Lumen, all of your law enforcement databases are neatly organized in a simple system, and our database experts can incorporate custom databases into the fold for more informational context and faster, easier access.

Try Lumen Today

Don’t just take the word of the crime analysts who use and love Lumen—try it out for yourself and see how Lumen can help your law enforcement agency close more cases and work more efficiently than ever before. Schedule a demo of Lumen today.